We compared the proposed A-PixelHop method with several state-of-the-art methods, including Cozzolino2017 [1]} and AutoGAN
with spectral input (Auto-Spec) [2]}. Here, we
follow the leave-one-out setting described in [2]}, [4]}, where one subset is set aside for
testing while the other nine subsets are used in the training process. Table REF  shows the test accuracy of the proposed method as well as the existing methods. We see that A-PixelHop reaches 100% accuracy for
five (out of ten) subsets. Its average accuracy over the 10 subsets is
98.7%, which is best among all methods.
